Nvidia launches new open models to run agents in the enterprise and on PCs
THE SO WHAT
Open models tuned for agents on both servers and PCs push more enterprises toward running their own stacks instead of relying solely on hosted assistants. If you're building internal agents, this is a prompt to reassess your on-prem vs SaaS balance and where you want data and execution to live.
READ THE SOURCE
MORE FROM THE WIRE
Applied AIPartnering with Blacksmith
If agents can write production-scale code, the new bottleneck is proving that code is safe, performant, and compliant at the same speed. Expect “agent-era CI/CD” vendors like Blacksmith to become a required layer in any serious agent deployment, not a nice-to-have devtool.
Applied AICoreWeave Upgraded to Buy at Goldman on Overblown Debt Worries
If public markets start treating CoreWeave’s leverage as manageable rather than existential, hyperscale AI infra looks more like a durable asset class than a bubble bet. For buyers, that supports multi-year commitments to alt-cloud GPU providers—though you should still price in refinancing and capacity risk, not assume hyperscaler-level stability.
Applied AIThinking More About AI and the Shale Boom Parallel
Treating AI like the shale boom reframes the question from ‘are we in a bubble?’ to ‘who captures the resource rents and who eats the capex hangover.’ Operators should be explicit about which side of that line they’re on—owning differentiated “resource” (data, distribution, infra) versus paying peak-cycle prices for commoditized capacity.
Applied AISources: DeepSeek and Huawei are collaborating on future AI chip designs; DeepSeek plans to start using Ascend 950DT for pre-training as soon as 2026's end
A model lab shaping Huawei’s Ascend 950DT roadmap is a direct attempt to close the loop between frontier training needs and domestic silicon—reducing dependence on US-controlled GPUs. Anyone exposed to China-facing AI demand should assume a more credible non-Nvidia path by 2027 and plan for a bifurcated tooling and optimization stack.